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系統識別號 U0026-0810201915460200
論文名稱(中文) 以多光譜影像觀察坡地果樹樹頂分布並進行植保無人機之遍歷路徑規劃
論文名稱(英文) Observing the tree top distribution of sloping fruit trees with multi-spectral imagery and conducting traversal path planning for plant protection drones
校院名稱 成功大學
系所名稱(中) 工程科學系
系所名稱(英) Department of Engineering Science
學年度 108
學期 1
出版年 108
研究生(中文) 邵子軒
研究生(英文) Zi-Xuan Shao
學號 N96064141
學位類別 碩士
語文別 中文
論文頁數 58頁
口試委員 指導教授-黃悅民
口試委員-黃顯詔
口試委員-陳靜茹
口試委員-張傳育
口試委員-張傳旺
中文關鍵字 多光譜  植保無人機  最大概似估計  蟻群系統  坡地  果樹 
英文關鍵字 Multi-spectral  plant protection drones  maximum likelihood estimation  ant colony systems  sloping fields  fruit trees 
學科別分類
中文摘要 近年來,植保無人機已漸漸商業化並廣泛於各種國家中進行使用,眾多廠商爭相投入研發,如大疆等公司已開發出可用於各種場合的各式無人機。在美國,以飛機搭載農藥並以空中投放農藥的方式進行農藥噴灑的方法已臻成熟,然而此種方法的限制便是噴灑農藥的農地須幅員遼闊才可以達到使用飛機有效率地噴灑農藥,若農地狹小且破碎,此種方法將不再可行,而台灣的梯田或是坡地更是限制了此種方法的實行。相對於條件較為嚴苛的使用飛機噴灑農藥方法,以植保無人機進行農藥噴灑的方式在台灣,因其更具彈性,可以應對台灣的主流農地地形,因此成為農民噴灑農藥時的選擇之一,近年來台灣農業從業人口老化,勞動力不足,且坡地地形需大量勞動力進行農藥噴灑,而傾斜的地勢也容易造成意外事故的發生,若以植保無人機進行,可節省勞動力,同時也保障了農民的安全。
本研究以各種多光譜圖片進行觀測與紀錄,使用最大概似估計法對多光譜的各種圖像進行物件的分類,在圖像的一隅找出特定物件在多光譜圖像中所呈現的特徵,並使用最大概似估計推估出整張多光譜圖像中各個物件的分布區域,並特別凸顯出龍眼樹的分布區域。
根據龍眼樹的分布大小及位置,以市售植保無人機的噴灑範圍為基準,設計出數個能保證植保無人機完整噴灑農藥於果樹的點作為無人機飛行時懸停的區域,並將這些點的座標以蟻群演算法中的蟻群系統進行路徑規劃,根據多次測試,測量出能經過所有懸停區域的最佳路徑。
英文摘要 In recent years, the agricultural population in Taiwan has been aging and the labor force is insufficient. The slope topography requires a large amount of labor to spray pesticides, and the inclined terrain is also likely to cause accidents. If planted with drones, it can save labor and protect farmers. Safety.
In this study, various multi-spectral images are used for observation and recording. The most approximate estimation method is used to classify various images of multi-spectral images, and the features of specific objects in multi-spectral images are found at a glance of the image. And use the most approximate estimation to estimate the distribution of each object in the entire multi-spectral image, and highlight the distribution of the longan tree.
According to the distribution size and location of the longan tree, based on the spray range of the commercially available plant protection drones, several points are designed to ensure that the plant protection drone completely sprays the pesticides on the fruit trees as the hovering area of the drone during flight. The coordinates of the points are routed by the ant colony system in the ant colony algorithm. According to multiple tests, the best path that can pass through all hovering areas is measured.
論文目次 摘要 I
Extended Abstract II
誌謝 IX
目錄 X
表目錄 XI
圖目錄 XII
第一章、緒論 1
1-1 研究動機與背景 1
1-2 研究目的 3
1-3 章節編排 3
第二章、文獻探討 5
2-1 多光譜圖像之語意分割 5
2-2 路徑規劃 14
第三章、系統設計 23
3-1 多光譜圖像之分類 23
3-2 根據目標範圍設點 25
3-3 路徑規劃 31
第四章、模擬運算實驗與實際環境實驗 32
4-1 語意分割 32
4-2 設立無人機懸空點 42
第五章、結論與未來展望 55
5-1 結論 55
5-2 未來展望 55
參考文獻 56
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